Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 65 270 727 359 149 965 466 333 953 484 921 721 170 297 656 398 271 951 980 86
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 333 359 398 721 270 953 86 965 484 170 NA 149 921 NA 297 65 656 727 980 951 466 271 NA
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 2 2 3 4 5 1 5 3 2 1
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "y" "x" "z" "v" "p" "M" "E" "U" "Z" "S"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 6 9 11 18 19
which( manyNumbersWithNA > 900 )
[1] 6 8 13 19 20
which( is.na( manyNumbersWithNA ) )
[1] 11 14 23
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 965 953 921 951 980
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 965 953 921 951 980
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 965 953 921 951 980
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "M" "E" "U" "Z" "S"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "y" "x" "z" "v" "p"
manyNumbers %in% 300:600
[1] FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE
[19] FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 4 7 8 10 16
sum( manyNumbers %in% 300:600 )
[1] 5
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "small" "small" "small" "large" "small" "large" "small" "large" "small" "small" NA "small" "large" NA
[15] "small" "small" "large" "large" "large" "large" "small" "small" NA
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "small" "small" "small" "large" "small" "large" "small" "large" "small" "small" "UNKNOWN"
[12] "small" "large" "UNKNOWN" "small" "small" "large" "large" "large" "large" "small" "small"
[23] "UNKNOWN"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 0 0 0 721 0 953 0 965 0 0 NA 0 921 NA 0 0 656 727 980 951 0 0 NA
unique( duplicatedNumbers )
[1] 2 3 4 5 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 2 3 4 5 1
duplicated( duplicatedNumbers )
[1] FALSE TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 19
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 980
which.min( manyNumbersWithNA )
[1] 16
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 65
range( manyNumbersWithNA, na.rm = TRUE )
[1] 65 980
manyNumbersWithNA
[1] 333 359 398 721 270 953 86 965 484 170 NA 149 921 NA 297 65 656 727 980 951 466 271 NA
sort( manyNumbersWithNA )
[1] 65 86 149 170 270 271 297 333 359 398 466 484 656 721 727 921 951 953 965 980
sort( manyNumbersWithNA, na.last = TRUE )
[1] 65 86 149 170 270 271 297 333 359 398 466 484 656 721 727 921 951 953 965 980 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 980 965 953 951 921 727 721 656 484 466 398 359 333 297 271 270 170 149 86 65 NA NA NA
manyNumbersWithNA[1:5]
[1] 333 359 398 721 270
order( manyNumbersWithNA[1:5] )
[1] 5 1 2 3 4
rank( manyNumbersWithNA[1:5] )
[1] 2 3 4 5 1
sort( mixedLetters )
[1] "E" "M" "p" "S" "U" "v" "x" "y" "z" "Z"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 3.5 8.5 8.5 8.5 5.0 8.5 6.0 1.5 3.5 1.5
rank( manyDuplicates, ties.method = "min" )
[1] 3 7 7 7 5 7 6 1 3 1
rank( manyDuplicates, ties.method = "random" )
[1] 4 10 9 8 5 7 6 1 3 2
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.0000000 -0.5000000 0.0000000 0.5000000 1.0000000 0.4625116 0.8043795 -0.5801799 0.7766542 -0.7421766
[11] 1.4632048 -0.3144051 0.5751103 -2.7669828 1.8633520
round( v, 0 )
[1] -1 0 0 0 1 0 1 -1 1 -1 1 0 1 -3 2
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 0.5 0.8 -0.6 0.8 -0.7 1.5 -0.3 0.6 -2.8 1.9
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 0.46 0.80 -0.58 0.78 -0.74 1.46 -0.31 0.58 -2.77 1.86
floor( v )
[1] -1 -1 0 0 1 0 0 -1 0 -1 1 -1 0 -3 1
ceiling( v )
[1] -1 0 0 1 1 1 1 0 1 0 2 0 1 -2 2
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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